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Xingxing Zhang

Microsoft Research

4 papers hereh-index 234.1k citations40 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • middle author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CL4
affiliations
  • Microsoft Research
Homepage
same name
  • Xingxing Zhang — 11 papers
  • Xingxing Zhang — 7 papers
  • Xingxing Zhang — 3 papers
  • Xingxing Zhang — 2 papers
  • Xingxing Zhang — 2 papers
  • Xingxing Zhang — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20182022
most citedHIBERT: Document Level Pre-training of Hierarchical Bidirectional Transformers for Document Summarization

51 citations · 64 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CL2022★ 13 cited

Momentum Calibration for Text Generation

Xingxing Zhang, Yiran Liu, Xun Wang +5

The input and output of most text generation tasks can be transformed to two sequences of tokens and they can be modeled using sequence-to-sequence learning modeling tools such as…

cs.CL2022

Neural Label Search for Zero-Shot Multi-Lingual Extractive Summarization

Ruipeng Jia, Xingxing Zhang, Yanan Cao +3

In zero-shot multilingual extractive text summarization, a model is typically trained on English summarization dataset and then applied on summarization datasets of other languages…

cs.CL2019★ 51 cited

HIBERT: Document Level Pre-training of Hierarchical Bidirectional Transformers for Document Summarization

Xingxing Zhang, Furu Wei, Ming Zhou

Neural extractive summarization models usually employ a hierarchical encoder for document encoding and they are trained using sentence-level labels, which are created heuristically…

cs.CL2018

Neural Latent Extractive Document Summarization

Xingxing Zhang, Mirella Lapata, Furu Wei +1

Extractive summarization models require sentence-level labels, which are usually created heuristically (e.g., with rule-based methods) given that most summarization datasets only h…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.